How localized are computational templates? A machine learning approach.
A commonly held background assumption about the sciences is that they connect along borders characterized by ontological or explanatory relationships, usually given in the order of mathematics, physics, chemistry, biology, psychology, and the social sciences. Interdisciplinary work, in this picture,...
| Publicado en: | Synthese Vol. 201; no. 3; pp. 1 - 23 |
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| Formato: | Artículo |
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Springer Nature
Mar2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=162455643&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 162455643 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Mar2023 vid: 201 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 162455643 10.1007/s11229-023-04057-x ppf: 1 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: P size: 4.2MB tig: atl: How localized are computational templates? A machine learning approach. aug: au: Noichl, Maximilian affil: Faculty of Philosophy and Education, University of Vienna, Universitätsstraße 7, 1010, Vienna, Austria Faculty for Social Sciences and Economics, University of Bamberg, Feldkirchenstraße 21, 96045, Bamberg, Germany sug: keyword: Computational philosophy Computational templates Digital humanities Formulas Model templates Modeling practice Science mapping ab: A commonly held background assumption about the sciences is that they connect along borders characterized by ontological or explanatory relationships, usually given in the order of mathematics, physics, chemistry, biology, psychology, and the social sciences. Interdisciplinary work, in this picture, arises in the connecting regions of adjacent disciplines. Philosophical research into interdisciplinary model transfer has increasingly complicated this picture by highlighting additional connections orthogonal to it. But most of these works have been done through case studies, which due to their strong focus struggle to provide foundations for claims about large-scale relations between multiple scientific disciplines. As a supplement, in this contribution, we propose to philosophers of science the use of modern science mapping techniques to trace connections between modeling techniques in large literature samples. We explain in detail how these techniques work, and apply them to a large, contemporary, and multidisciplinary data set (n=383.961 articles). Through the comparison of textual to mathematical representations, we suggest formulaic structures that are particularly common among different disciplines and produce first results indicating the general strength and commonality of such relationships. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2023. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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